Smart Control Rooms: Detecting Deepfakes and Emotions with AI
Salma Farès (Technical Research Chair, InterTalk™ Critical Information Systems)
Location: N257
Date: Monday, March 17
Time: 10:50 am - 11:20 am
Track: First Responders
Topics: AI, Cloud, Cybersecurity, IoT, LMR, NG911, PTT, Situational Awareness
Format: Power Session
Vault Recording: TBD
In today's high-stakes control rooms, where critical communication systems manage emergency responses and ensure operational stability, artificial intelligence (AI) emerges as a key asset. Among the various AI applications, speech emotion recognition (SER) stands particularly beneficial. With SER, control rooms can better identify the emotional urgency of calls and ensure that distress calls are prioritized and handled appropriately. Voice deepfakes detection (VDD) is also essential, as it helps identify synthetic voices that could mislead operators and emergency responders.
By integrating SER and VDD, control rooms can develop a more effective communication verification system. SER can assess the emotional urgency of the caller's distress, while VDD identifies synthetic voices to prioritize resource allocation. However, integrating SER and VDD into critical communication systems presents several challenges. The technology must operate with high precision and reliability, as any misinterpretation could have severe consequences. It needs to accommodate a range of voices and communication styles, including different languages and accents. Additionally, strong data privacy and cybersecurity measures are required to protect sensitive information. Despite these challenges, the potential benefits of AI-driven SER-VDD make it a valuable tool for modern control rooms. In this presentation, explore the role of AI in critical communication systems, delve into the specific advantages and applications of SER and VDD, and address the potential challenges associated with implementing these technologies in high-stress environments.
Takeaway
Takeaway 1: AI significantly boosts efficiency in mission-critical control rooms by automating tasks and processing data rapidly, leading to better decision-making and response.
Takeaway 2: Speech Emotion Recognition (SER) analyzes vocal cues to assess the emotional state of callers, allowing dispatchers to tailor their responses based on the caller's emotional urgency.
Takeaway 3: Voice Deepfakes Detection (VDD) identifies synthetic voices, preventing deceptive or misleading calls from diverting attention and resources away from real emergencies.
Takeaway 4: Combining SER and VDD strengthens communication verification systems, reducing the risk of false alarms and improving the prioritization and management of real emergencies.